Two-Stage Robust Optimization for Integrated Energy Systems with Bidirectional Demand Response and Tiered Carbon Trading
二段階ロバスト最適化を用いた統合エネルギーシステムの双方向デマンドレスポンスと段階的炭素取引 (AI 翻訳)
Xiaohua Song, Tong Liu, Tianyu Wu, Lu Zhang
🤖 gxceed AI 要約
日本語
本論文は、風力発電、CHP、炭素回収、P2Gを組み合わせた統合エネルギーシステムに対し、段階的炭素取引メカニズムと双方向デマンドレスポンスを組み込んだ二段階ロバスト最適化手法を提案する。不確実性を調整可能な集合で表現し、列生成アルゴリズムで求解。ケーススタディでは、炭素排出量を50.40%削減し、需要応答によりピークオフ差を150kW低減することを示した。
English
This paper develops a two-stage robust optimization method for park-level integrated energy systems with tiered carbon trading and bidirectional demand response. Case studies show 50.40% carbon emission reduction and 150 kW peak-valley difference reduction, effectively balancing economy and robustness.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本のGX文脈では、段階的炭素取引（類似の仕組みは日本でも議論中）とデマンドレスポンスの統合的運用の参考になる。ただし、システム規模や電力市場構造が異なるため、直接適用には調整が必要。
In the global GX context
Globally, this paper contributes a robust optimization framework that explicitly models carbon pricing tiers alongside demand response, relevant for integrated energy systems planning under uncertainty.
👥 読者別の含意
🔬研究者:Provides a rigorous optimization model combining carbon trading and demand response, useful for further research in energy system scheduling.
🏢実務担当者:Offers a method to reduce carbon emissions and peak loads, applicable for park-level energy management.
🏛政策担当者:Demonstrates the effectiveness of tiered carbon pricing in reducing emissions, supporting policy design for carbon markets.
📄 Abstract（原文）
Amid accelerating energy transition and carbon reduction goals, integrated energy systems offer multi-energy complementary to enhance efficiency and reduce carbon emissions. This paper develops a park-level integrated energy systems model incorporating wind power, combined heat and power, carbon capture, and Power to Gas, proposing a two-stage robust scheduling method integrating a tiered carbon trading mechanism and bidirectional demand response. Adjustable uncertainty sets characterize renewable and load fluctuations, with the Column and Constraint Generation algorithm ensures tractable optimization. Case studies demonstrate that the tiered carbon pricing mechanism reduces carbon emissions by 50.40% (from 44,052.73 kg to 21,827.00 kg) and carbon costs by 5.40%. The Demand Response Mechanism with energy storage reduces the electricity load peak–valley difference by 150 kW and electricity purchase costs by 4.60%, effectively improving flexibility and system balance. Although total operating cost rises slightly by 5.84% compared to deterministic optimization, the robustness and operational safety of scheduling are significantly enhanced. The proposed methods promote the coordinated operation of the electricity-carbon system, optimizing economic dispatch, and address uncertainties.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1115/1.4071615first seen 2026-05-05 22:46:45
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